ScLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data.

ABSTRACT: A system-level understanding of the regulation and coordination mechanisms of gene expression is essential for studying the complexity of biological processes in health and disease. With the rapid development of single-cell RNA sequencing technologies, it is now possible to investigate gene interactions in a cell type-specific manner. Here we propose the scLink method, which uses statistical network modeling to understand the co-expression relationships among genes and construct sparse gene co-expression networks from single-cell gene expression data. We use both simulation and real data studies to demonstrate the advantages of scLink and its ability to improve single-cell gene network analysis. The scLink R package is available at https://github.com/Vivianstats/scLink.

SUBMITTER: Vivian Li W 

PROVIDER: S-EPMC8896229 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature